We met both our supervisors with some expert people both from Chalmers and Volvo-Cars.
- We presented our thesis work (research, problems, ideas,..) to the new visitors.
- Patrizio (docent in SW Enginering) introduced himself and his works about software models (dependencies).
- We discussed about the concept "readability" and agreed that it depends on the targeted audience. In our case the audience is 'developers of the DURA team' meaning that they have a certain understanding about technique and diagrams and they will validate our research's outcomes. It is important to show our test results to them to understand what is more readable in their case.
- Truong (Phd candidate) presented his work : A tool generating UML class diagrams with different abstraction levels. His tool uses machine learning to define the 'importance' of each components. Depending on the abstraction parameter, items with less importance disappear.
- We decided to study Truong's solution and see if his concepts can be adapted to our case. We will try to define the importance of every component in our models and see if it produces acceptable results. The difficulty is that given the limited number of models we have (7), it will be hard to use his machine learning algorithm.
- We decided to meet in two weeks to present our progress before everyone goes on summer vacations.
- We should also think about some research questions.
Comments:
ReplyDelete- With regards to the audiences: The DURA team should be considered as the one who validate your research's outcomes.
- Regarding the concept "Readability": Need to be consistent and concrete from the beginning - That's very important and vulnerable of subjectivity.
- About the idea of using machine learning: "Item" should be "component". Therefore, the number of components is more important than number of models.
Questions:
- Did you write something?
- Did you try importing the component diagram to SDMetrics?
- Let's drop by my office if you need any helps.
/Truong.